Sleep quality can provide certain influence to human health. Monitoring at least some physiological parameters in sleeping may not only evaluate the sleep quality, but also provide a valuable diagnostic basis for certain conditions and/or diseases. Thus, analyzing and achieving the non-contact method for monitoring sleep can be of a significant importance.
The monitoring process of the conventional methods and systems for monitoring sleep can include collecting body movement signals from a person to be monitored. A fixed threshold based estimation can be performed each time one signal is collected, to determine a sleep state which the person to be monitored is currently at. If each time one signal is collected, the estimation can performed one time, the collected signal may be subject to an interference. Therefore, an error may be generated in the estimation, and resulting in the counted data is not reliable. There may be different distances from a sensor to the person to be monitored, it causes the sensitivity deviation of the sensor; in addition, the adaptive ability of the fixed threshold based estimation is poor. Thus, the sleep state of the person to be monitored may not be monitored accurately. Accordingly, the conventional methods for monitoring sleep have poor anti-inference ability, poor adaptive ability and/or results in unreliable monitoring result. Further, the conventional methods for monitoring sleep may not meet the preference of strong adaptive ability and highly reliable sleep monitoring application.
Accordingly, there is a need to address at least some of the issued and/or deficiencies described herein above.